This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
At the end of this course, participants will be able to:
• Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
• Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform
• Employ BigQuery and Cloud Datalab to carry out interactive data analysis
• Choose between Cloud SQL, BigTable and Datastore
• Train and use a neural network using TensorFlow
• Choose between different data processing products on the Google Cloud Platform
Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:
• A common query language such as SQL
• Extract, transform, load activities
• Data modeling
• Machine learning and/or statistics
• Programming in Python
Google Account Notes:
• You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google services are currently unavailable in China).
• If you are a Google Cloud Platform customer with European Union (EU) and Russian billing addresses, read the VAT Overview documentation at: https://cloud.google.com/billing/docs/resources/vat-overview
• More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
Introduction to the Data and Machine Learning on Google Cloud Platform Specialization
Module 1: Introduction to Google Cloud Platform and its Big Data Products In this module you will be introduced to Google Cloud Platform and the data handling aspects of the platform.
Module 2: Foundations of GCP Compute and Storage In this module, we introduce the foundations of the Google Cloud Platform: compute and storage and introduce how they work to provide data ingest, storage, and federated analysis.
Module 3: Data Analysis on the Cloud In this module we introduce the common Big Data use cases that Google will manage for you. These are the things that are widely done in industry today and for which we provide easy migration to the cloud.
Module 4: Scaling Data Analysis: Compute with GCP This module is about the more transformational technologies in Google Cloud platform that may not have immediate parallels to technologies that attendees are using (“what's next”).
Module 5: Data Processing Architectures: Scalable Ingest, Transform and Load In this module we will introduce you to data processing architectures in Google Cloud Platform: Asynchronous processing with TaskQueues. Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow.
Module 6: Summary of Google Cloud Platform, Big Data, and ML
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
Y. Nicodemepartially completed this course, spending 5 hours a week on it and found the course difficulty to be easy.
This course materials and in particular its organization were very deceptive. Google Cloud platform looks like a great platform, but the tutorials and examples are no different from what you'd fine by opening a free account at Google Cloud platform.